Abstract
We consider the use of a database cluster for high-performance support of Online Analytical Processing (OLAP) applications. OLAP intra-query parallelism can be obtained by partitioning the database tables across cluster nodes. We propose to combine physical and virtual partitioning into a partitioning scheme called Adaptive Hybrid Partitioning (AHP). AHP requires less disk space while allowing for load balancing. We developed a prototype for OLAP parallel query processing in database clusters using AHP. Our experiments on a 32-node database cluster using the TPC-H benchmark demonstrate linear and super-linear speedup. Thus, AHP can reduce significantly the execution time of typical OLAP queries.
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